Telegram RegisterThe public register of Telegram

Channel

不求甚解

@fakeye

On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry

19,332subscribers

-34 since we began measuring on 6 August 2026

Risers and fallers across the register · movement among entries of 10,000–31,623.

Register entry

Telegram ID-1001280703189
TypeChannel
Username@fakeye
Description👀 在这里分享我日常的所见所思。 by @somkanel 📰 RSS 订阅: https://rss.fakeye.xyz 💻 镜像站: https://channel.fakeye.xyz 📖 博客(每日更新):https://blog.solazy.me 🎄 帮助频道助力: https://t.me/fakeye?boost ⚠️ 别在评论里发表低智/政治倾向/杠精言论,会被拉黑(关注关系是双向的)。 🚫 本频道不接广告。
Created1 November 2019measured — cross-checked against a third-party dataset (TGDataset)
First recorded6 August 2026
Last confirmed live12 August 2026
Measurements held8
Confirmed unchanged1 time, most recently 12 August 2026
On Telegramt.me/fakeye

Growth

19,33219,36619,3496 August 2026 — 19,366 subscribers7 August 2026 — 19,362 subscribers8 August 2026 — 19,354 subscribers9 August 2026 — 19,352 subscribers10 August 2026 — 19,349 subscribers10 August 2026 — 19,344 subscribers11 August 2026 — 19,337 subscribers12 August 2026 — 19,332 subscribers6 August 202612 August 2026
8 measurements spanning 6 days, net -34. Dots are measurements; the straight line between them is drawn to join them, not to claim we know the path taken in between — snapshots are recorded only when a count changes, so gaps mean “no change observed”, never “interpolated”. The vertical axis spans 19,327–19,371 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
12 Aug 2026, 18:4819,332-5
11 Aug 2026, 21:2419,337-7
10 Aug 2026, 22:4519,344-5
10 Aug 2026, 01:2319,349-3
9 Aug 2026, 01:2019,352-2
8 Aug 2026, 03:1219,354-8
7 Aug 2026, 00:2219,362-4
6 Aug 2026, 12:4519,366first reading

Engagement

18 posts held, back to 14 January 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 18 pagesof Telegram’s post history, 20 posts per page.

Nothing published in the last 30 days. ERR and ER are rolling 30-day measures, so there is nothing to compute — we hold 18 posts for this entry, the most recent from 30 June 2026. An engagement rate over an empty window would be a number about nothing.

What this channel posts

Photos
1,470
Videos
28
Links
609

Lifetime counters from Telegram’s own channel header, read 13 August 2026 — not the date at the top of this page, which is when the subscriber count was last read. A count marked was rounded by Telegram before we ever saw it — t.me prints these counters in full below 1,000 and to three significant figures above, so ≈142,000 means somewhere between 141,500 and 142,499.

Video runtime
1m 31s
Average length
30s

Measured directly from 3 videos with a duration reading, out of the posts we hold for this channel — not this channel’s whole posting history, only the sample this register has actually read. An exact reading to the second, taken from the post itself rather than from Telegram’s own rounded chrome, so it carries no mark.

Reaction mix

325 reactions across 18 posts, in 12 distinct kinds. The most used accounts for 36.9% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
12036.9%
👍9428.9%
👏237.08%
🤝226.77%
💋216.46%
💅175.23%
🦄154.62%
🔥61.85%
🍓20.615%
😐20.615%
🤔20.615%
🥰10.308%

No sentiment is inferred, and none should be read in. This table is ordered by count and by nothing else. Emoji do not carry stable meaning across languages or communities — 🙏 is thanks in one channel and mourning in another — so we publish which ones were pressed and how often, and pass no judgement on what an audience meant by them.

Precision. Telegram publishes reaction counts per emoji and short-forms each one — 4.34K, 1.2M — so any single kind at or above 1,000 reaches us at three significant figures, and only counts below 1,000 are exact. The shares above are ratios of those figures and carry the same error. This is also why the total here can differ slightly from a reaction total printed elsewhere on the page: both are sums of the same rounded parts, taken over samples with different edges.

Coverage. Reactions were read on 18 of the 18 sampled posts in this sample. Summed by Telegram’s own count on each post — not by adding up the per-emoji breakdown above — those same posts carry 325reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 18 most recent posts we hold, published 14 January 2026 to 30 June 2026, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.

Recent posts

30 Jun 2026, 10:45 UTC≈4,880 views15 reactionsread 13 August 2026
Photo

#APP #iOS #Shortcuts 🎧 接群友 Aaron 投稿,今天分享一个专为 AirPods Max 用户准备的快捷指令。 🔗 AirPods Max Companion 💬 AirPods Max 的音质和降噪一直没什么可挑剔的,不过想暂停音乐、切歌、切换通透模式时,很多人还是会下意识去摸耳机,或者打开控制中心。相比当年 EarPods 线控那种盲操作的体验,总觉得少了点顺手。 👆 这个快捷指令就是为了解决这个问题。它把 iPhone 的【操作按钮】和音量键组合成一套类似 iPod nano 7 / EarPods 线控的组合键,不改变 AirPods Max 原本的按键逻辑,也不需要安装第三方 App。 📖 导入快捷指令后,将它分配给 iPhone 的【操作按钮】。首次运行时,根据提示选择两次 AirPods Max 的噪声控制路径即可。 之后可以这样操作: • 单按【操作按钮】:暂停音乐并切换到通

👍85🦄2

30 Apr 2026, 02:32 UTC≈8,870 views15 reactionsread 13 August 2026
Photo

#Mac #Android #App 👩‍💻 无缝连接你的 Mac 和 Android —— AndDrive AndDrive 是一款旨在打破 Android 手机与 macOS 之间的生态壁垒,通过深度系统集成,实现文件管理、高清投屏和高效协作。 🧙‍♂️ 特性 •深度集成 Finder:将 Android 设备直接挂载为 Mac 的一个“本地磁盘”。用户可以在 Finder 侧边栏直接读写手机文件,支持拖拽、系统快捷键及 macOS 原生的空格键“快速预览”功能。 • 高清实时投屏:提供低延迟的手机屏幕与音频投射功能。用户可以直接在 Mac 桌面端呼出 Android 应用列表,并启动任意 App。 • 剪贴板同步:支持 Mac 与 Android 之间的双向文本和图片同步,复制粘贴无需中转。 • 输入法共享:允许在 Android App 中直接使用 Mac 的键盘和输入法,完美支持中文输入及 Emoji。 •

15

16 Apr 2026, 02:44 UTC≈9,200 views18 reactionsread 13 August 2026
Photo

#Mac #App ✏️ AI 驱动的轻量级 Markdown 编辑器 —— marknow 📻 marknow 是 Anyway.FM 主播 Leon 的新作品,它是一款 Markdown 编辑器。 🧙‍♂️ 特性 • Markdown 实时语法高亮 + 代码块背景 • 内置 AI 助手(支持 Gemini / OpenAI / Claude / XiaomiMimo) • @Ai 行内提问(回车触发) • 选中文本多轮讨论 • RAG 记忆库 — 本地 TF-IDF 索引,跨笔记上下文检索 • Mermaid 图表实时预览 • MCP 外部工具集成 👩‍💻 目前 maknow 只提供 Mac 版本,可以通过 项目页面 进行下载。

👍162

15 Apr 2026, 04:00 UTC≈7,670 views13 reactionsread 13 August 2026
Photo

#Life #Movie 🍿 《迈克尔·杰克逊:巨星之路》开票了,都给我冲!

💋121

14 Apr 2026, 11:27 UTC≈7,310 views24 reactionsread 13 August 2026
Video

#Web 🍎 生成苹果风格的「hello」文本动画 🏄‍♀️ 今天网上冲浪的时候发现了一个有趣的项目,作者是 Kumail Nanji 它在自己的网站上开放了一个 Playground,可以在这个页面里生成使用任意字母生成 Apple 风格的手写「hello」动画。 💡 页面还明确的写出了作者在制作这个动画项目的一些试错和花絮。

👍11💋92🍓2

10 Apr 2026, 08:41 UTC≈7,730 views15 reactionsread 13 August 2026
Photo

#Life #Music 🎵 什么叫双厨狂喜啊朋友们 🌝

15

20 Mar 2026, 02:01 UTC≈9,400 views20 reactionsread 13 August 2026
Photo

#Blog #Web #GitHub 🍿 在博客展示观影记录 —— Movies 页面持续折腾记 🎬 有经常看我博客的朋友可能会发现,我前段时间在博客真增加了一个「Movies」页面,这个页面主要是用来展示我的观影记录。数据源就是我的豆瓣已看片单。 🫛 如果你恰好也有这样的需求,并且自己使用日常标记已看影片的服务使用的也是豆瓣,那么可以参考我下面的三则折腾日志。如果你还没有开始建立这个习惯,那么我觉得你可以尝试使用 NeoDB 这类开放性更强的服务,来代替豆瓣(我个人之所以不换 NeoDB 是基于使用习惯来考虑的,其实迁移很方便,有 豆伴/豆坟 这类的工具。 🧱 我的折腾日志们: • 博客新增「Movies」页面(2026.1.27) • 又迭代了一下博客的「Movies」页面(2026.2.9) • 彻底重构了博客的豆瓣观影同步机制(2026.3.18) ☝️ 另外,最近的一次折腾的导火索是发现 GitHub Ac

👏128

19 Mar 2026, 03:19 UTC≈7,180 views19 reactionsread 13 August 2026
Photo

#Web 📚 不仅是翻译工具,而是你的多语言思考伙伴 —— Kagi 翻译 👀 Kagi 翻译 是一款基于先进大模型能力打造的在线翻译与语言助手,集「文本翻译」「校对润色」「词典查询」「文档翻译」「网页翻译」于一体。无论是查一句话、润色一段文案,还是直接阅读外文网页、长文档,Kagi 翻译都可以帮助你在不同语言之间快速切换,同时尽可能保留原文的语气和信息密度。 🧙‍♂️ 特性: • 多模式一体:提供文本翻译、校对润色、词典查询、文档翻译、网页翻译等完整能力,覆盖从一句话到整篇文档、整站内容的多种场景。 • 懂语境的智能翻译:基于大模型理解上下文,不做死板直译,更注重语气、语感与信息密度,还原「像人写的」表达。 • 风格与趣味语言支持:支持彩蛋玩法,可以自己键入目标语言(比如我自己尝试了「阿里黑话」「主理人语气」「郭语」等),支持在同一语言内部做风格迁移和话术改写,适合职场沟通、品牌文案和社交内容。 • 翻译历史与收藏:自

🦄136

10 Mar 2026, 02:00 UTC≈8,020 views20 reactionsread 13 August 2026
Photo

#Web #Life 🚄 还可以这样 —— 铁路12306积分延期工具 💡 今天介绍一个邪修类的技能,名字如题,说是工具,其实这个网页就纯粹是一个规则普及和操作手册。 🧙‍♂️ 其实这里利用的是一个规则漏洞,让用户查询当天晚点的列车车次,并根据建议购票时间(需要让发车时间大于当前时间 30 分钟)使用积分兑换车票,并马上完成退票,积分兑换购票时会优先使用即将过期的积分,而退票又会让积分重新入账,从而做到变相延期。 🤔 之所以称之为邪修,就是因为这并非是一个绝对正常的积分延期途径,并且伴有诸多风险(例如:一天只能退票3次,还要考虑到我可能会退其他车票等)。本人并不提倡,但是介绍这个项目是想告诉大家,其实很多功能实现都是独立且很难兼容异常流的,以及 12306 的积分使用手动开通才能积的。 👉 你可以前往项目线上 实例 查看更多具体信息,如若使用请务必看完开发者写下的所有文字,并检查待办列表中的注意事项。

20

24 Feb 2026, 08:04 UTC≈9,150 views32 reactionsread 13 August 2026
Photo

#GitHub #Apple #Web #iOS 🍎 多区 Apple Store 下载管理神器—— AssppWeb 🔍 AssppWeb 是一款基于网页的工具,用于在 App Store 之外获取和安装 iOS 应用。使用您的 Apple ID 进行身份验证,搜索应用,获取许可证,并将 IPA 文件直接安装到您的设备上。 🤫 简而言之,就是通过该项目使用 Apple ID 登录,就可以在非 App Store 内下载并安装 App。适合拥有多区 App Store 账号,并使用多区独有 App 的用户。尤其是在 iOS 26.4 Beta 中,多区 App Storte 切换难度显著上升的情况,和前阵子多个字节跳动下的国区 App 纷纷在外区下架的场景下。 来自项目的安全技术科普: AssppWeb采用零信任设计,其中服务器永远不会看到您的 Apple 凭证所有 Apple API 通信均直接在您的浏览器中通过 W

👍257

16 Feb 2026, 11:54 UTC≈8,480 views38 reactionsread 13 August 2026
Photo

#Life 🧧 新春快乐,朋友们!

🤝22👍123😐1

28 Jan 2026, 08:01 UTC≈11,900 views22 reactionsread 13 August 2026
Video

#Web 🚗 用浏览器感受 TESLA 车机 —— TeslaUI 直接使用桌面浏览器打开 TeslaUI,可以感受绝大部分车机功能,使用键盘上的 C 键充电,D 键挂挡行驶。 2020 年款阿童木车主哭晕在厕所。

👍21😐1

Showing the 12 most recent of 18 posts we hold for @fakeye. View and reaction counts are the latest single reading for each post, not a live figure, and a recent post is still accumulating both. A view count marked was rounded by Telegram before we ever saw it — t.me prints views in full below 1,000 and to three significant figures above, so ≈1,200,000 means somewhere between 1,150,000 and 1,249,999. Unmarked counts are exact. Text is reproduced from the public post preview and truncated for length.

Citation-graph rank

Citation-graph rank — 276,752 of 1,169,250entries in the measured graph. A weighted position computed from the forward and mention edges below — republished posts weigh more than named mentions — and recomputed periodically, over the whole graph. Published only as this ordinal position, never as a score: a position is a fact, and a score printed beside one channel’s name would read as a verdict this register does not make. The two counts beneath stay separate for the same reason mentions are never summed with forwards anywhere else on this page — a named-by count costs nothing to manufacture. The top 100 by this measure, or how it is computed.

Forward network

Republished by

Channels on the register that have forwarded this channel's posts into their own feed.

Built only from forwarded posts we have actually read, on both sides. Coverage is early and deliberately incomplete: a missing link means we have not read the post that would prove it, never that the relationship does not exist. Counts are distinct forwarded posts observed, so they only ever go up as we read more.

Mentions

Named by 6 registered channels — every channel on the register whose own posts have named this one, by its current username or any other username it currently holds, merged from two separately captured readings of the same fact so a namer caught by only one of them is not missed and a namer both caught is not counted twice. A username this channel has since dropped is not matched — that handle may belong to someone else now, and crediting today’s namer to yesterday’s owner would misattribute it.

A mention is a weaker signal than a forward and is counted separately for that reason — naming a channel is not republishing it, and a handle in a post body is easy to place deliberately. The post counts beside each row below are distinct posts in which the handle appeared, from posts we have read on both sides — the “Named by N registered channels” figure above is a different count, of distinct NAMING CHANNELS rather than posts, and is not the sum of the rows under it.

Cite this entry

A live page changes as we take new readings, so a citation should name the measurement it is based on, not just the URL. The line below cites the subscriber count as measured 12 August 2026 — this entry's latest reading, not the date you are reading this.

“不求甚解” (@fakeye), 19,332 subscribers as measured 12 August 2026. Telegram Register, tgregister.com/channel/fakeye.

Full measurement history, CC BY 4.0. Every reading this register holds for this entry, not just the latest one, as a dated, downloadable record: CSV · JSON. Free to use with attribution to tgregister.com. Each file carries its own generation timestamp, which is the figure to cite for exactly when the data was retrieved.